Hemispheric asymmetries and prosodic emotion recognition deficits in Parkinson's disease

Changes in speech prosody perception during Parkinson's disease: A comprehensive analysis

INTRODUCTION

Parkinson's disease (PD) is a progressive neurodegenerative disorder that affects approximately 1%-2% of individuals aged 60 and above. Communication disorders in PD can significantly impact the overall quality of life. As prosody plays a vital role in verbal communication, the present study examines Persian prosody perception in PD, focusing on linguistic and emotional aspects of prosody.

METHODS

This cross-sectional study aimed to compare the perception of linguistic and emotional prosody in three groups: middle-aged adults (n = 22; mean age = 50.40 years), healthy older adults (n = 22; mean age = 68.31 years), and individuals with Parkinson's disease (n = 22; mean age = 65years). All individuals with PD were classified in stages 1; 1.5; 2; 2.5, and 3 of the disease using the Hoehn and Yahr scale. All participants had an MMSE score of 24 or above. The Florida Affect Battery (FAB) was used to evaluate prosody perception. This Battery was validated in the Persian language and its reliability and validity were reported as 94 % and 100 % respectively.

RESULTS

Participants with PD presented significantly lower scores than the older adults in all subtests of the FAB (p < 0.05), while healthy older adults were significantly different only in linguistic discrimination (β = -2.14; -3.68 to -0.61), and linguistic naming of prosody (β = 1.25; 0.17 to 2.33) compared to middle-aged adults.

CONCLUSIONS

The present study sheds light on the influence of PD on Persian prosody perception. Given the crucial role of prosody in verbal communication, these findings enhance our understanding of communication disorders in PD and could bring attention to consider prosody perception, among other aspects, when assessing individuals affected by PD.

Crossed functional specialization between the basal ganglia and cerebellum during vocal emotion decoding: Insights from stroke and Parkinson’s disease

There is growing evidence that both the basal ganglia and the cerebellum play functional roles in emotion processing, either directly or indirectly, through their connections with cortical and subcortical structures. However, the lateralization of this complex processing in emotion recognition remains unclear. To address this issue, we investigated emotional prosody recognition in individuals with Parkinson’s disease (model of basal ganglia dysfunction) or cerebellar stroke patients, as well as in matched healthy controls (n = 24 in each group). We analysed performances according to the lateralization of the predominant brain degeneration/lesion. Results showed that a right (basal ganglia and cerebellar) hemispheric dysfunction was likely to induce greater deficits than a left one. Moreover, deficits following left hemispheric dysfunction were only observed in cerebellar stroke patients, and these deficits resembled those observed after degeneration of the right basal ganglia. Additional analyses taking disease duration / time since stroke into consideration revealed a worsening of performances in patients with predominantly right-sided lesions over time. These results point to the differential, but complementary, involvement of the cerebellum and basal ganglia in emotional prosody decoding, with a probable hemispheric specialization according to the level of cognitive integration.

Longitudinal clustering analysis and prediction of Parkinson's disease progression using radiomics and hybrid machine learning

BACKGROUND

We employed machine learning approaches to (I) determine distinct progression trajectories in Parkinson's disease (PD) (unsupervised clustering task), and (II) predict progression trajectories (supervised prediction task), from early (years 0 and 1) data, making use of clinical and imaging features.

METHODS

We studied PD-subjects derived from longitudinal datasets (years 0, 1, 2 & 4; Parkinson's Progressive Marker Initiative). We extracted and analyzed 981 features, including motor, non-motor, and radiomics features extracted for each region-of-interest (ROIs: left/right caudate and putamen) using our standardized standardized environment for radiomics analysis (SERA) radiomics software. Segmentation of ROIs on dopamine transposer - single photon emission computed tomography (DAT SPECT) images were performed via magnetic resonance images (MRI). After performing cross-sectional clustering on 885 subjects (original dataset) to identify disease subtypes, we identified optimal longitudinal trajectories using hybrid machine learning systems (HMLS), including principal component analysis (PCA) + K-Means algorithms (KMA) followed by Bayesian information criterion (BIC), Calinski-Harabatz criterion (CHC), and elbow criterion (EC). Subsequently, prediction of the identified trajectories from early year data was performed using multiple HMLSs including 16 Dimension Reduction Algorithms (DRA) and 10 classification algorithms.

RESULTS

We identified 3 distinct progression trajectories. Hotelling's t squared test (HTST) showed that the identified trajectories were distinct. The trajectories included those with (I, II) disease escalation (2 trajectories, 27% and 38% of patients) and (III) stable disease (1 trajectory, 35% of patients). For trajectory prediction from early year data, HMLSs including the stochastic neighbor embedding algorithm (SNEA, as a DRA) as well as locally linear embedding algorithm (LLEA, as a DRA), linked with the new probabilistic neural network classifier (NPNNC, as a classifier), resulted in accuracies of 78.4% and 79.2% respectively, while other HMLSs such as SNEA + Lib_SVM (library for support vector machines) and t_SNE (t-distributed stochastic neighbor embedding) + NPNNC resulted in 76.5% and 76.1% respectively.

CONCLUSIONS

This study moves beyond cross-sectional PD subtyping to clustering of longitudinal disease trajectories. We conclude that combining medical information with SPECT-based radiomics features, and optimal utilization of HMLSs, can identify distinct disease trajectories in PD patients, and enable effective prediction of disease trajectories from early year data.

Deficits in emotion perception and cognition in patients with parkinson's disease: A systematic review

Non-motor symptoms (NMS) are common among Parkinson's disease (PD) patients and have a significant impact on quality of life. NMS such as deficits in emotion perception are gaining due focus in the recent times. As emotion perception and cognitive functions share certain common neural substrates, it becomes pertinent to evaluate existing emotion perception deficits in view of underlying cognitive deficits. The current systematic review aimed at examining studies on emotion perception PD in the last decade. We carried out a systematic review of 44 studies from the PubMed database. We reviewed studies examining emotion perception and associated cognitive deficits, especially executive function and visuospatial function in PD. This review also examines how early and advanced PD differ in emotion perception deficits and how the presence of common neuropsychiatric conditions such as anxiety, apathy, and depression as well as neurosurgical procedure such as deep brain stimulation affect emotion perception. The need for future research employing a comprehensive evaluation of neurocognitive functions and emotion perception is underscored as it has a significant bearing on planning holistic intervention strategies.

The enigma and implications of brain hemispheric asymmetry in neurodegenerative diseases

The lateralization of the human brain may provide clues into the pathogenesis and progression of neurodegenerative diseases. Though differing in their presentation and underlying pathologies, neurodegenerative diseases are all devastating and share an intriguing theme of asymmetrical pathology and clinical symptoms. Parkinson’s disease, with its distinctive onset of motor symptoms on one side of the body, stands out in this regard, but a review of the literature reveals asymmetries in several other neurodegenerative diseases. Here, we review the lateralization of the structure and function of the healthy human brain and the common genetic and epigenetic patterns contributing to the development of asymmetry in health and disease. We specifically examine the role of asymmetry in Parkinson’s disease, Alzheimer’s disease, amyotrophic lateral sclerosis, and multiple sclerosis, and interrogate whether these imbalances may reveal meaningful clues about the origins of these diseases. We also propose several hypotheses for how lateralization may contribute to the distinctive and enigmatic features of asymmetry in neurodegenerative diseases, suggesting a role for asymmetry in the choroid plexus, neurochemistry, protein distribution, brain connectivity and the vagus nerve. Finally, we suggest how future studies may reveal novel insights into these diseases through the lens of asymmetry.

Detection of hypomimia in patients with Parkinson's disease via smile videos

Background

Parkinson’s disease (PD) is a neurodegenerative disease characterized by the impairment of facial expression, known as hypomimia. Hypomimia has serious impacts on patients’ ability to communicate, and it is difficult to detect at early stages of the disease. Furthermore, due to bradykinesia or other reasons, it is inconvenient for PD patients to visit the hospital. Therefore, it is appealing to develop an auxiliary diagnostic method that remotely detects hypomimia.

Methods

We proposed an automatic detection system for Parkinson’s hypomimia based on facial expressions (DSPH-FE). DSPH-FE provides a convenient remote service for those who potentially suffer from hypomimia and only requires patients to input their facial videos. Specifically, patients can detect hypomimia through two aspects: geometric features and texture features. Geometric features focus on visually representing structures of facial muscles. Facial expression factors (FEFs) are used as the first metric to quantify the current activation state of the facial muscles. Facial expression change factors (FECFs) are subsequently used as the second metric to calculate the moving trajectories of the activation states in the videos. Geometric features primarily concentrate on spatial information, with little involvement of temporal information. Thus, the extended histogram of oriented gradients (HOG) algorithm is introduced. This algorithm can extract texture features within multiple continuous frames and incorporate the temporal information into the features. Finally, these features are applied to four machine learning algorithms to model the relationship between these features and hypomimia.

Results

The DSPH-FE detection system achieved the best performance when concatenating geometric features and texture features, resulting in a F1 score of 0.9997. The best F1 scores achieved with geometric features and texture features were 0.8286 and 0.9446, respectively. This indicated that both geometric features and texture features have an ability to predict hypomimia, and demonstrated that temporal information can boost the model performance. Thus, DSPH-FE is an effective supportive tool in the medical management of PD patients.

Conclusions

Comprehensive experiments demonstrated that proposed features fit well with real-world videos and are beneficial in the clinical diagnosis of hypomimia. In particular, hypomimia had a greater impact on eyes and mouths when patients are smiling.

Feature selection and machine learning methods for optimal identification and prediction of subtypes in Parkinson's disease

OBJECTIVES

The present work focuses on assessment of Parkinson's disease (PD), including both PD subtype identification (unsupervised task) and prediction (supervised task). We specifically investigate optimal feature selection and machine learning algorithms for these tasks.

METHODS

We selected 885 PD subjects as derived from longitudinal datasets (years 0-4; Parkinson's Progressive Marker Initiative), and investigated 981 features including motor, non-motor, and imaging features (SPECT-based radiomics features extracted using our standardized SERA software). Two different hybrid machine learning systems (HMLS) were constructed and applied to the data in order to select optimal combinations in both tasks: (i) identification of subtypes in PD (unsupervised-clustering), and (ii) prediction of these subtypes in year 4 (supervised-classification). From the original data based on years 0 (baseline) and 1, we created new datasets as inputs to the prediction task: (i,ii) CSD0 and CSD01: cross-sectional datasets from year 0 only and both years 0 & 1, respectively; (iii) TD01: timeless dataset from both years 0 & 1. In addition, PD subtype in year 4 was considered as outcome. Finally, high score features were derived via ensemble voting based on their prioritizations from feature selector algorithms (FSAs).

RESULTS

In clustering task, the most optimal combinations (out of 981) were selected by individual FSAs to enable high correlation compared to using all features (arriving at 547). In prediction task, we were able to select optimal combinations, resulting in an accuracy >90% only for timeless dataset (TD01); there, we were able to select the most optimal combination using 77 features, directly selected by FSAs. In both tasks, however, using combination of only high score features from ensemble voting did not enable acceptable performances, showing optimal feature selection via individual FSAs to be more effective.

CONCLUSION

Combining non-imaging information with SPECT-based radiomics features, and optimal utilization of HMLSs, can enable robust identification of subtypes as well as appropriate prediction of these subtypes in PD patients. Moreover, use of timeless dataset, beyond cross-sectional datasets, enabled predictive accuracies over 90%. Overall, we showed that radiomics features extracted from SPECT images are important in clustering as well as prediction of PD subtypes.

Robust identification of Parkinson's disease subtypes using radiomics and hybrid machine learning

OBJECTIVES

It is important to subdivide Parkinson's disease (PD) into subtypes, enabling potentially earlier disease recognition and tailored treatment strategies. We aimed to identify reproducible PD subtypes robust to variations in the number of patients and features.

METHODS

We applied multiple feature-reduction and cluster-analysis methods to cross-sectional and timeless data, extracted from longitudinal datasets (years 0, 1, 2 & 4; Parkinson's Progressive Marker Initiative; 885 PD/163 healthy-control visits; 35 datasets with combinations of non-imaging, conventional-imaging, and radiomics features from DAT-SPECT images). Hybrid machine-learning systems were constructed invoking 16 feature-reduction algorithms, 8 clustering algorithms, and 16 classifiers (C-index clustering evaluation used on each trajectory). We subsequently performed: i) identification of optimal subtypes, ii) multiple independent tests to assess reproducibility, iii) further confirmation by a statistical approach, iv) test of reproducibility to the size of the samples.

RESULTS

When using no radiomics features, the clusters were not robust to variations in features, whereas, utilizing radiomics information enabled consistent generation of clusters through ensemble analysis of trajectories. We arrived at 3 distinct subtypes, confirmed using the training and testing process of k-means, as well as Hotelling's T2 test. The 3 identified PD subtypes were 1) mild; 2) intermediate; and 3) severe, especially in terms of dopaminergic deficit (imaging), with some escalating motor and non-motor manifestations.

CONCLUSION

Appropriate hybrid systems and independent statistical tests enable robust identification of 3 distinct PD subtypes. This was assisted by utilizing radiomics features from SPECT images (segmented using MRI). The PD subtypes provided were robust to the number of the subjects, and features.

Subthalamic nucleus oscillations during vocal emotion processing are dependent of the motor asymmetry of Parkinson's disease

The subthalamic nucleus (STN) is involved in different aspects of emotional processes and more specifically in emotional prosody recognition. Recent studies on the behavioral effects of deep brain stimulation (DBS) in patients with Parkinson's disease (PD) have uncovered an asymmetry in vocal emotion decoding in PD, with left-onset PD patients showing deficits for the processing of happy voices. Whether and how PD asymmetry affects STN electrophysiological responses to emotional prosody, however, remains unknown. In the current study, local field potential activity was recorded from eight left- and six right-lateralized motor-onset PD patients (LOPD/ROPD) undergoing DBS electrodes implantation, while they listened to angry, happy and neutral voices. Time-frequency decomposition revealed that theta (2-6 Hz), alpha (6-12 Hz) and gamma (60-150 Hz) band responses to emotion were mostly bilateral with a differential pattern of response according to patient's sides-of onset. Conversely, beta-band (12-20 Hz and 20-30 Hz) emotional responses were mostly lateralized in the left STN for both patient groups. Furthermore, STN theta, alpha and gamma band responses to happiness were either absent (theta band) or reduced (alpha and gamma band) in the most affected STN hemisphere (contralateral to the side-of onset), while a late low-beta band left STN happiness-specific response was present in ROPD patients and did not occur in LOPD patients. Altogether, in this study, we demonstrate a complex pattern of oscillatory activity in the human STN in response to emotional voices and reveal a crucial influence of disease laterality on STN low-frequency oscillatory activity.

Social perceptual function in parkinson's disease: A meta-analysis

Social perceptual impairment is a common presenting feature of Parkinson's disease (PD) that has the potential to contribute considerably to disease burden. The current study reports a meta-analytic integration of 79 studies which shows that, relative to controls, PD is associated with a moderate emotion recognition deficit (g = -0.57, K = 73), and that this deficit is robust and almost identical across facial and prosodic modalities. However, the magnitude of this impairment does appear to vary as a function of task and emotion type, with deficits generally greatest for identification tasks (g = -0.65, K = 54), and for negative relative to other basic emotions. With respect to clinical variables, dopaminergic medication, deep brain stimulation, and a predominant left side onset of motor symptoms are each associated with greater social perceptual difficulties. However, the magnitude of social perceptual impairment seen for the four atypical parkinsonian conditions is broadly comparable to that associated with PD. The theoretical and practical implications of these findings are discussed.

Cortical Thickness Alterations in Chronic Pain Disorder: An Exploratory MRI Study

OBJECTIVE

Chronic pain disorder (CPD) has been associated with brain changes, especially in limbic circuits. However, in most patients with chronic pain, depression or anxiety is a common comorbidity. In this exploratory and naturalistic study, we investigated brain cortical thickness (CTh) differences between patients with CPD and healthy controls, with consideration of concurrent psychiatric symptoms.

METHODS

Twenty-three patients with CPD and 23 age- and sex-matched healthy volunteers were included in this study. CTh was estimated using Freesurfer on high-resolution three-dimensional T1-weighted images acquired with a 3T scanner. Group differences were investigated using an analysis of covariance model that included age, sex, and Beck Depression Inventory I and Trait Anxiety Inventory scores as covariates. The relationship between CTh and Toronto Alexithymia Scale (TAS-20) scores was also investigated in patients. Data were corrected for multiplicity using the False Discovery Rate approach (q < .05).

RESULTS

The comparison between groups using demographics and Beck Depression Inventory I scores as covariates showed thinner cortex in patients compared with controls, after correction for multiplicity in the left precentral (F(1,42) = 21.9, p < .05) and postcentral gyri (F(1,42) = 26.9, p < .05) and in the left inferior temporal sulcus (F(1,42) = 19.6, p < .05). Moreover, using the Trait Anxiety Inventory as covariate, a trend toward significance (p < .001 uncorrected) was seen for the left precentral gyrus (F(1,42) = 13.8), right middle frontal (F(1,42) = 14.3) and inferior parietal gyri (F(1,42) = 13.4), and right anterior temporal pole (F(1,42) = 15.9).

CONCLUSIONS

The results indicate that brain morphological differences between patients with chronic pain disorder and healthy controls are localized to regions that correspond to sensory as well as affective dimensions of pain processing.

Facial emotion recognition in Parkinson's disease: A review and new hypotheses

Parkinson's disease is a neurodegenerative disorder classically characterized by motor symptoms. Among them, hypomimia affects facial expressiveness and social communication and has a highly negative impact on patients' and relatives' quality of life. Patients also frequently experience nonmotor symptoms, including emotional-processing impairments, leading to difficulty in recognizing emotions from faces. Aside from its theoretical importance, understanding the disruption of facial emotion recognition in PD is crucial for improving quality of life for both patients and caregivers, as this impairment is associated with heightened interpersonal difficulties. However, studies assessing abilities in recognizing facial emotions in PD still report contradictory outcomes. The origins of this inconsistency are unclear, and several questions (regarding the role of dopamine replacement therapy or the possible consequences of hypomimia) remain unanswered. We therefore undertook a fresh review of relevant articles focusing on facial emotion recognition in PD to deepen current understanding of this nonmotor feature, exploring multiple significant potential confounding factors, both clinical and methodological, and discussing probable pathophysiological mechanisms. This led us to examine recent proposals about the role of basal ganglia-based circuits in emotion and to consider the involvement of facial mimicry in this deficit from the perspective of embodied simulation theory. We believe our findings will inform clinical practice and increase fundamental knowledge, particularly in relation to potential embodied emotion impairment in PD. © 2018 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Dopamine drives left-hemispheric lateralization of neural networks during human speech

Although the concept of left-hemispheric lateralization of neural processes during speech production has been known since the times of Broca, its physiological underpinnings still remain elusive. We sought to assess the modulatory influences of a major neurotransmitter, dopamine, on hemispheric lateralization during real-life speaking using a multimodal analysis of functional MRI, intracranial EEG recordings, and large-scale neural population simulations based on diffusion-weighted MRI. We demonstrate that speech-induced phasic dopamine release into the dorsal striatum and speech motor cortex exerts direct modulation of neuronal activity in these regions and drives left-hemispheric lateralization of speech production network. Dopamine-induced lateralization of functional activity and networks during speaking is not dependent on lateralization of structural nigro-striatal and nigro-motocortical pathways. Our findings provide the first mechanistic explanation for left-hemispheric lateralization of human speech that is due to left-lateralized dopaminergic modulation of brain activity and functional networks.

Neurocircuitry of impaired affective sound processing: A clinical disorders perspective

Decoding affective meaning from sensory information is central to accurate and adaptive behavior in many natural and social contexts. Human vocalizations (speech and non-speech), environmental sounds (e.g. thunder, noise, or animal sounds) and human-produced sounds (e.g. technical sounds or music) can carry a wealth of important aversive, threatening, appealing, or pleasurable affective information that sometimes implicitly influences and guides our behavior. A deficit in processing such affective information is detrimental to adaptive environmental behavior, psychological well-being, and social interactive abilities. These deficits can originate from a diversity of psychiatric and neurological disorders, and are associated with neural dysfunctions across largely distributed brain networks. Recent neuroimaging studies in psychiatric and neurological patients outline the cortical and subcortical neurocircuitry of the complimentary and differential functional roles for affective sound processing. This points to and confirms a recently proposed distributed network rather than a single brain region underlying affective sound processing, and highlights the notion of a multi-functional process that can be differentially impaired in clinical disorders.

Facial emotion recognition in Parkinson's disease: Association with age and olfaction

OBJECTIVE

The ability to recognize facial emotion expressions has been reported to be impaired in Parkinson's disease (PD), yet previous studies showed inconsistent findings. The aim of this study was to further investigate facial emotion recognition (FER) in PD patients and its association with demographic and clinical parameters (including motor and nonmotor symptoms).

METHOD

Thirty-four nondemented PD patients and 24 age- and sex-matched healthy controls (HC) underwent clinical neurological and neuropsychological assessment, standardized olfactory testing with Sniffin' Sticks, and the Ekman 60 Faces Emotion Recognition Test.

RESULTS

PD patients had a significantly lower score on the total FER task than HC (p = .006), even after controlling for the potential confounding factors depression and apathy. The PD group had a specific impairment in the recognition of surprise (p = .007). The recognition of anger approached statistical significance (p = .07). Increasing chronological age and age at disease onset were associated with worse performance on the FER task in PD patients. Olfactory function along with PD diagnosis predicted worse FER performance within all study participants.

CONCLUSION

Facial emotion recognition and especially the recognition of surprise are significantly impaired in PD patients compared with age- and sex-matched HC. The association of FER with age and olfactory function is endorsed by common structures that undergo neurodegeneration in PD. The relevance of FER in social interaction stresses the clinical relevance and the need for further investigation in this field. Future studies should also determine whether impaired FER is already present in premotor stages of PD.

Reception of Communicative Functions of Prosody in Hypokinetic Dysarthria due to Parkinson's Disease

BACKGROUND

Mapping adequacy of receptive prosodic abilities in speakers with hypokinetic dysarthria due to Parkinson's disease (PD) is useful, because therapy of disturbed production of prosody relies on adequate reception of prosody. There is evidence for a deficit of reception of emotional prosody in PD.

OBJECTIVE

The present study aims at presenting a comprehensive picture of the reception of various communicative functions of prosody in hypokinetic dysarthria due to PD.

METHODS

We assessed perception (using a discrimination task) and comprehension (using an identification task) of five communicative functions of Dutch prosody (lexical stress, boundary marking, focus, sentence mode, and emotional prosody) in a group of adults with hypokinetic dysarthria due to PD (n = 22) and a gender and age matched group of unimpaired adults (n = 22). We also investigated the relationship between age and global test score, and the effect of perception and comprehension subtest sequence on the global test score.

RESULTS

Between groups, no significant differences in receptive prosodic abilities were found. Within both groups, the comprehension subtest was significantly more difficult than the perception subtest, and there was a significant negative correlation between age and global test score. No subtest sequence effect could be demonstrated.

CONCLUSIONS

Considering that the older speakers with hypokinetic dysarthria due to PD had receptive prosodic skills inferior to those of the younger speakers, notwithstanding apparently intact cognition and hearing, the findings suggest that age is a factor to be reckoned with in prosody assessment and management in this population.

Side-of-onset of Parkinson's disease in relation to neuropsychological measures

BACKGROUND

Parkinson's disease (PD) usually emerges with a unilateral side-of-onset (left-onset: LOPD; right-onset: ROPD; Marinus & van Hilten, 2015) due to an asymmetrical degeneration of striatal dopaminergic neurons (Donnemiller et al., Brain, 135, 2012, 3348). This has led to a body of research exploring the cognitive, neuropsychological, and clinical differences between LOPD and ROPD (e.g., Verreyt et al., Neuropsychology Review, 21, 2011, 405).

METHODS

Thirty ROPD and 14 LOPD cases were drawn from a Boston clinic specializing in PD. Various cognitive and neuropsychological measures were used in an attempt to discover if there were indeed any differences between LOPD and ROPD in this cohort.

RESULTS

For LOPD, duration of illness was found to be significantly greater than that of ROPD. However, further testing was able to confirm that despite this difference, it was not the cause of the other significant differences found. Furthermore, this increased duration was consistent with a previous study (Munhoz et al., Parkinsonism and Related Disorders, 19, 2013, 77). Performance on the Digit Span Backward (DSB) was found to be significantly poorer in LOPD than ROPD, suggesting compromised executive function in LOPD. Additionally, LOPD had significantly greater anxiety on the DASS Anxiety scales than ROPD. However, unlike Foster et al (Cognitive and Behavioral Neurology, 23, 2010, 4), this increased anxiety could not account for the poorer performance on the DSB for LOPD. Finally, ROPD had significantly greater magical ideation than LOPD, which can be explained by the theory put forth by Brugger and Graves (European Archives of Psychiatry, 247, 1997, 55).

CONCLUSION

Clear and significant differences between LOPD and ROPD were found within our cohort. LOPD showed greater impairment of working memory, greater anxiety, and greater duration of illness-all independent of one another; whereas, those with ROPD had greater magical ideation, also independent of any other variables.

Speech dysprosody but no music 'dysprosody' in Parkinson's disease

Parkinson's disease is characterized not only by bradykinesia, rigidity, and tremor, but also by impairments of expressive and receptive linguistic prosody. The facilitating effect of music with a salient beat on patients' gait suggests that it might have a similar effect on vocal behavior, however it is currently unknown whether singing is affected by the disease. In the present study, fifteen Parkinson patients were compared with fifteen healthy controls during the singing of familiar melodies and improvised melodic continuations. While patients' speech could reliably be distinguished from that of healthy controls matched for age and gender, purely on the basis of aural perception, no significant differences in singing were observed, either in pitch, pitch range, pitch variability, and tempo, or in scale tone distribution, interval size or interval variability. The apparent dissociation of speech and singing in Parkinson's disease suggests that music could be used to facilitate expressive linguistic prosody.

Strength Is in Numbers: Can Concordant Artificial Listeners Improve Prediction of Emotion from Speech?

Humans can communicate their emotions by modulating facial expressions or the tone of their voice. Albeit numerous applications exist that enable machines to read facial emotions and recognize the content of verbal messages, methods for speech emotion recognition are still in their infancy. Yet, fast and reliable applications for emotion recognition are the obvious advancement of present ‘intelligent personal assistants’, and may have countless applications in diagnostics, rehabilitation and research. Taking inspiration from the dynamics of human group decision-making, we devised a novel speech emotion recognition system that applies, for the first time, a semi-supervised prediction model based on consensus. Three tests were carried out to compare this algorithm with traditional approaches. Labeling performances relative to a public database of spontaneous speeches are reported. The novel system appears to be fast, robust and less computationally demanding than traditional methods, allowing for easier implementation in portable voice-analyzers (as used in rehabilitation, research, industry, etc.) and for applications in the research domain (such as real-time pairing of stimuli to participants’ emotional state, selective/differential data collection based on emotional content, etc.).

Experiential and Doctrinal Religious Knowledge Categorization in Parkinson's Disease: Behavioral and Brain Correlates

Recent studies suggest changes in religious cognition in a subgroup of patients with Parkinson's disease (PD e.g., Butler et al., 2011). It is unclear whether this deficit extends to both doctrinal and experiential categorization forms of religious cognition. Kapogiannis et al. (2009b) dissociated experiential and doctrinal religious knowledge to different neural networks using fMRI. We examined Kapogiannis' dissociation against the background of PD side of onset (LOPD, ROPD), assessing performance both On- and Off-medication. In the behavioral portion of the study, we used a statement classification task in combination with scholar derived test sets for experiential and doctrinal religious knowledge categorization in conjunction with neuropsychological measures. In the neuroimaging portion of the study, we expanded on Kapogiannis' study by examining the same networks in PD. The behavioral data revealed that all groups rated (categorized) the scholar derived tests of experiential and doctrinal significantly differently than the scholars. All groups, including the scholars, classified more phrases as doctrinal than experiential. Religious cognition differed in the PD groups: those with PD Off-medication and LOPD Off-medication comprehended scholar defined experiential phrases with more difficulty, making them more likely to be classified as mixed or doctrinal. This was in contrast to the subjective frequency of classification of phrases as experiential paired with a cognitive decline in PD Off-medication; whereas PD On-medication showed a positive correlation with cognitive state and subjective doctrinal classification. For ROPD, cognitive state was associated with subjective experiential and doctrinal frequency of classification. With more intact intellect, there was a greater likelihood of classifying phrases subjectively as mixed, and the converse for experiential. Furthermore, religiosity negatively predicted subjective doctrinal frequency in LOPD, with the converse in ROPD. In fcMRI in PD, we found resting state functional intrinsic connectivity of reward networks associated with classification of statements using seeds in bilateral nucleus accumbens in PD. For experiential regressors, there was a negative correlation in bilateral frontal lobes paired with a positive correlation in left occipital visual areas (BAs 17, 18). For doctrinal regressors, there was a positive correlation in right BA 20.

Hemispheric asymmetry non-linear analysis of EEG during emotional responses from idiopathic Parkinson's disease patients

Recent studies show right hemisphere has a unique contribution to emotion processing. The present study investigated EEG using non-linear measures during emotional processing in PD patients with respect to motor symptom asymmetry (i.e., most affected body side). We recorded 14-channel wireless EEGs from 20 PD patients and 10 healthy age-matched controls (HC) by eliciting emotions such as happiness, sadness, fear, anger, surprise and disgust. PD patients were divided into two groups, based on most affected body side and unilateral motor symptom severity: left side-affected (LPD, n = 10) or right side-affected PD patients (RPD, n = 10). Nonlinear analysis of these emotional EEGs were performed by using approximate entropy, correlation dimension, detrended fluctuation analysis, fractal dimension, higher order spectra, hurst exponent (HE), largest Lyapunov exponent and sample entropy. The extracted features were ranked using analysis of variance based on F value. The ranked features were then fed into classifiers namely fuzzy K-nearest neighbor and support vector machine to obtain optimal performance using minimum number of features. From the experimental results, we found that (a) classification performance across all frequency bands performed well in recognizing emotional states of LPD, RPD, and HC; (b) the emotion-specific features were mainly related to higher frequency bands; and (c) predominantly LPD patients (inferred right-hemisphere pathology) were more impaired in emotion processing compared to RPD, as showed by a poorer classification performance. The results suggest that asymmetric neuronal degeneration in PD patients may contribute to the impairment of emotional communication.

Advanced Parkinson disease patients have impairment in prosody processing

BACKGROUND

The ability to recognize and interpret emotions in others is a crucial prerequisite of adequate social behavior. Impairments in emotion processing have been reported from the early stages of Parkinson's disease (PD). This study aims to characterize emotion recognition in advanced Parkinson's disease (APD) candidates for deep-brain stimulation and to compare emotion recognition abilities in visual and auditory domains.

METHOD

APD patients, defined as those with levodopa-induced motor complications (N = 42), and healthy controls (N = 43) matched by gender, age, and educational level, undertook the Comprehensive Affect Testing System (CATS), a battery that evaluates recognition of seven basic emotions (happiness, sadness, anger, fear, surprise, disgust, and neutral) on facial expressions and four emotions on prosody (happiness, sadness, anger, and fear). APD patients were assessed during the "ON" state. Group performance was compared with independent-samples t tests.

RESULTS

Compared to controls, APD had significantly lower scores on the discrimination and naming of emotions in prosody, and visual discrimination of neutral faces, but no significant differences in visual emotional tasks.

CONCLUSION

The contrasting performance in emotional processing between visual and auditory stimuli suggests that APD candidates for surgery have either a selective difficulty in recognizing emotions in prosody or a general defect in prosody processing. Studies investigating early-stage PD, and the effect of subcortical lesions in prosody processing, favor the latter interpretation. Further research is needed to understand these deficits in emotional prosody recognition and their possible contribution to later behavioral or neuropsychiatric manifestations of PD.

Discriminating facial expressions of emotion and its link with perceiving visual form in Parkinson's disease

We investigated the link between the ability to perceive facial expressions of emotion and the ability to perceive visual form in Parkinson's disease (PD). We assessed in individuals with PD and healthy controls the ability to discriminate graded intensities of facial expressions of anger from neutral expressions and the ability to discriminate radial frequency (RF) patterns with modulations in amplitude from a perfect circle. Those with PD were, as a group, impaired relative to controls in discriminating graded intensities of angry from neutral expressions and discriminating modulated amplitudes of RF patterns from perfect circles; these two abilities correlated positively and moderately to highly, even after removing the variance that was shared with disease progression and general cognitive functioning. The results indicate that the impaired ability to perceive visual form is likely to contribute to the impaired ability to perceive facial expressions of emotion in PD, and that both are related to the progression of the disease.

On the analysis of EEG power, frequency and asymmetry in Parkinson's disease during emotion processing

OBJECTIVE

While Parkinson's disease (PD) has traditionally been described as a movement disorder, there is growing evidence of disruption in emotion information processing associated with the disease. The aim of this study was to investigate whether there are specific electroencephalographic (EEG) characteristics that discriminate PD patients and normal controls during emotion information processing.

METHOD

EEG recordings from 14 scalp sites were collected from 20 PD patients and 30 age-matched normal controls. Multimodal (audio-visual) stimuli were presented to evoke specific targeted emotional states such as happiness, sadness, fear, anger, surprise and disgust. Absolute and relative power, frequency and asymmetry measures derived from spectrally analyzed EEGs were subjected to repeated ANOVA measures for group comparisons as well as to discriminate function analysis to examine their utility as classification indices. In addition, subjective ratings were obtained for the used emotional stimuli.

RESULTS

Behaviorally, PD patients showed no impairments in emotion recognition as measured by subjective ratings. Compared with normal controls, PD patients evidenced smaller overall relative delta, theta, alpha and beta power, and at bilateral anterior regions smaller absolute theta, alpha, and beta power and higher mean total spectrum frequency across different emotional states. Inter-hemispheric theta, alpha, and beta power asymmetry index differences were noted, with controls exhibiting greater right than left hemisphere activation. Whereas intra-hemispheric alpha power asymmetry reduction was exhibited in patients bilaterally at all regions. Discriminant analysis correctly classified 95.0% of the patients and controls during emotional stimuli.

CONCLUSION

These distributed spectral powers in different frequency bands might provide meaningful information about emotional processing in PD patients.

An ERP study of vocal emotion processing in asymmetric Parkinson's disease

Parkinson's disease (PD) has been related to impaired processing of emotional speech intonation (emotional prosody). One distinctive feature of idiopathic PD is motor symptom asymmetry, with striatal dysfunction being strongest in the hemisphere contralateral to the most affected body side. It is still unclear whether this asymmetry may affect vocal emotion perception. Here, we tested 22 PD patients (10 with predominantly left-sided [LPD] and 12 with predominantly right-sided motor symptoms) and 22 healthy controls in an event-related potential study. Sentences conveying different emotional intonations were presented in lexical and pseudo-speech versions. Task varied between an explicit and an implicit instruction. Of specific interest was emotional salience detection from prosody, reflected in the P200 component. We predicted that patients with predominantly right-striatal dysfunction (LPD) would exhibit P200 alterations. Our results support this assumption. LPD patients showed enhanced P200 amplitudes, and specific deficits were observed for disgust prosody, explicit anger processing and implicit processing of happy prosody. Lexical speech was predominantly affected while the processing of pseudo-speech was largely intact. P200 amplitude in patients correlated significantly with left motor scores and asymmetry indices. The data suggest that emotional salience detection from prosody is affected by asymmetric neuronal degeneration in PD.

Asymmetric right/left encoding of emotions in the human subthalamic nucleus

Emotional processing is lateralized to the non-dominant brain hemisphere. However, there is no clear spatial model for lateralization of emotional domains in the basal ganglia. The subthalamic nucleus (STN), an input structure in the basal ganglia network, plays a major role in the pathophysiology of Parkinson's disease (PD). This role is probably not limited only to the motor deficits of PD, but may also span the emotional and cognitive deficits commonly observed in PD patients. Beta oscillations (12–30 Hz), the electrophysiological signature of PD, are restricted to the dorsolateral part of the STN that corresponds to the anatomically defined sensorimotor STN. The more medial, more anterior and more ventral parts of the STN are thought to correspond to the anatomically defined limbic and associative territories of the STN. Surprisingly, little is known about the electrophysiological properties of the non-motor domains of the STN, nor about electrophysiological differences between right and left STNs. In this study, microelectrodes were utilized to record the STN spontaneous spiking activity and responses to vocal non-verbal emotional stimuli during deep brain stimulation (DBS) surgeries in human PD patients. The oscillation properties of the STN neurons were used to map the dorsal oscillatory and the ventral non-oscillatory regions of the STN. Emotive auditory stimulation evoked activity in the ventral non-oscillatory region of the right STN. These responses were not observed in the left ventral STN or in the dorsal regions of either the right or left STN. Therefore, our results suggest that the ventral non-oscillatory regions are asymmetrically associated with non-motor functions, with the right ventral STN associated with emotional processing. These results suggest that DBS of the right ventral STN may be associated with beneficial or adverse emotional effects observed in PD patients and may relieve mental symptoms in other neurological and psychiatric diseases.